地理研究

地理研究 ›› 2013, Vol. 32 ›› Issue (12): 2179-2188.doi: 10.11821/dlyj201312013

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区域植被覆盖的多尺度空间变异性——以贵州喀斯特高原为例

高江波1, 吴绍洪1, 蔡运龙2   

  1. 1. 中国科学院地理科学与资源研究所, 北京100101;
    2. 北京大学城市与环境学院, 北京100871
  • 收稿日期:2012-12-17 修回日期:2013-07-24 出版日期:2013-12-10 发布日期:2013-12-10
  • 作者简介:高江波（1984- ），男，山东临沂人，博士，助理研究员，主要从事喀斯特石漠化空间变异与退化机理研究。E-mail：gaojiangbo@igsnrr.ac.cn
  • 基金资助:
    国家自然科学基金资助项目（41301089）；国家科技支撑计划项目（2012BAC19B10）；中国科学院战略性先导科技专项课题（XDA05090307）

Investigating the spatial heterogeneity of vegetation cover at multi-scales：A case study in karst Guizhou Plateau of China

GAO Jiangbo1, WU Shaohong1, CAI Yunlong2   

  1. 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • Received:2012-12-17 Revised:2013-07-24 Online:2013-12-10 Published:2013-12-10

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摘要： 地理格局尺度依赖性的客观存在，要求在连续尺度序列上对区域植被覆盖空间变异性进行考察，以真实反映植被覆盖空间特征。以贵州喀斯特高原为例，借助地统计学和GIS 软件，揭示了研究区NDVI的空间变异特征，并进行了空间变异与空间尺度的耦合研究。结论如下：① NDVI空间变异程度表现出明显的尺度依存性，空间尺度的粗粒化对NDVI的平滑作用非常显著，但两种重采样方法对原始数据的粗粒化作用机制不同；② 基于不同遥感数据源获得的NDVI数据之间空间格局差异明显，而且传统统计结果与地统计学结果明显不同，说明空间信息对数据间的差异性统计影响显著；③ NDVI空间变异性呈现显著的各向异性，并表现出对遥感数据源的敏感性。

关键词: 植被覆盖, 空间变异性, 多尺度, 贵州喀斯特高原

Abstract: The scale-dependence of geographical pattern requires that research on the spatial heterogeneity of vegetation cover should be conducted at multi-scales. Based on the satellite-derived Normalized Difference Vegetation Index (NDVI), this paper applied Geographic Information System (GIS) and Geostatistics (GS) softwares to investigate the scale-dependence, isotropy and anisotropy of spatial heterogeneity of vegetation cover, with a case study of Guizhou Karst Plateau. The main conclusions can be drawn as follows. (1) The spatial heterogeneity of NDVI was significantly scale-dependent because scale coarsening had remarkable smoothing effects on NDVI. However, the mechanism of data coarsening was different between two kinds of resampling methods. (2) There were differences in the spatial patterns of NDVI between RS data sources. The comparative results from traditional statistics and geostatistics for three NDVI datasets were different, indicating that spatial information is very important for statistical analysis. (3) Spatial heterogeneity of NDVI was accompanied with anisotropy, which was sensitive to RS sources. The important impact of altitude, precipitation and bio-temperature on the macro spatial distribution of NDVI also changed with spatial directions. The research findings are helpful for rocky desertification controlling and ecological reconstruction.

Key words: vegetation cover, spatial heterogeneity, multi-scales, karst Guizhou Plateau